Segment anything model for head and neck tumor segmentation with CT, PET and MRI multi-modality images

arXiv:2402.17454v1 Announce Type: cross
Abstract: Deep learning presents novel opportunities for the auto-segmentation of gross tumor volume (GTV) in head and neck cancer (HNC), yet fully automatic methods usually necessitate significant manual refinement. This study investigates the Segment Anything Model (SAM), recognized for requiring minimal human prompting and its zero-shot generalization ability across natural images. We specifically examine MedSAM, a version of SAM fine-tuned with large-scale public medical images. Despite its progress, the integration of multi-modality images (CT, PET, MRI) …

abstract arxiv auto cancer cs.cv deep learning head images mri novel opportunities pet physics.med-ph sam segment segment anything segment anything model segmentation study type